Our research goal is to design systems that enable humans to teach tedious, repetitive, simple tasks to a computer. We propose here a learner/problem solver architecture for such ...
Most symbolic classifiers aim at building sets of rules with good coverage and precision. While this is suitable for most applications, they tend to neglect other desirable proper...
Rafael Giusti, Gustavo E. A. P. A. Batista, Ronald...
This paper introduces GSSS (Genetic State-Space Search). The integration of two general search paradigms — genetic search and state-space-search provides a general framework whi...
In order to solve nonstationary optimization problems efficiently, evolutionary algorithms need sufficient diversity to adapt to environmental changes. The dual-population genetic...
Rational decision making requires full knowledge of the utility function of the person affected by the decisions. However, in many cases, the task of acquiring such knowledge is n...